Application of the Hurricane Optimization Algorithm to Estimate Parameters in Single-Phase Transformers Considering Voltage and Current Measures
In this research paper, a combinatorial optimization approach is proposed for parameter estimation in single-phase transformers considering voltage and current measurements at the transformer terminals. This problem is represented through a nonlinear programming model (NLP), whose objective is to mi...
- Autores:
-
Cortés-Caicedo, Brandon
Montoya, Oscar Danilo
Arias-Londoño, Andrés
- Tipo de recurso:
- Fecha de publicación:
- 2022
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/12275
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/12275
https://doi.org/10.3390/computers11040055
- Palabra clave:
- Transformer Windings;
Frequency Response;
Electric Potential
LEMB
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
| id |
UTB2_be04f9a7b20cbade5014865cf1ee64a3 |
|---|---|
| oai_identifier_str |
oai:repositorio.utb.edu.co:20.500.12585/12275 |
| network_acronym_str |
UTB2 |
| network_name_str |
Repositorio Institucional UTB |
| repository_id_str |
|
| dc.title.spa.fl_str_mv |
Application of the Hurricane Optimization Algorithm to Estimate Parameters in Single-Phase Transformers Considering Voltage and Current Measures |
| title |
Application of the Hurricane Optimization Algorithm to Estimate Parameters in Single-Phase Transformers Considering Voltage and Current Measures |
| spellingShingle |
Application of the Hurricane Optimization Algorithm to Estimate Parameters in Single-Phase Transformers Considering Voltage and Current Measures Transformer Windings; Frequency Response; Electric Potential LEMB |
| title_short |
Application of the Hurricane Optimization Algorithm to Estimate Parameters in Single-Phase Transformers Considering Voltage and Current Measures |
| title_full |
Application of the Hurricane Optimization Algorithm to Estimate Parameters in Single-Phase Transformers Considering Voltage and Current Measures |
| title_fullStr |
Application of the Hurricane Optimization Algorithm to Estimate Parameters in Single-Phase Transformers Considering Voltage and Current Measures |
| title_full_unstemmed |
Application of the Hurricane Optimization Algorithm to Estimate Parameters in Single-Phase Transformers Considering Voltage and Current Measures |
| title_sort |
Application of the Hurricane Optimization Algorithm to Estimate Parameters in Single-Phase Transformers Considering Voltage and Current Measures |
| dc.creator.fl_str_mv |
Cortés-Caicedo, Brandon Montoya, Oscar Danilo Arias-Londoño, Andrés |
| dc.contributor.author.none.fl_str_mv |
Cortés-Caicedo, Brandon Montoya, Oscar Danilo Arias-Londoño, Andrés |
| dc.subject.keywords.spa.fl_str_mv |
Transformer Windings; Frequency Response; Electric Potential |
| topic |
Transformer Windings; Frequency Response; Electric Potential LEMB |
| dc.subject.armarc.none.fl_str_mv |
LEMB |
| description |
In this research paper, a combinatorial optimization approach is proposed for parameter estimation in single-phase transformers considering voltage and current measurements at the transformer terminals. This problem is represented through a nonlinear programming model (NLP), whose objective is to minimize the root mean square error between the measured voltage and current values and the calculated values from the equivalent model of the single-phase transformer. These values of voltage and current can be determined by applying Kirchhoff’s Laws to the model T of the transformer, where its parameters, series resistance and reactance as well as the magnetization resistance and reactance, i.e., R1, R′2,X1, X′2,Rc y Xm, are provided by the Hurricane Optimization Algorithm (HOA). The numerical results in the 4 kVA, 10 kVA and 15 kVA single-phase test transformers demonstrate the applicability of the proposed method since it allows the reduction of the average error between the measured and calculated electrical variables by 1000% compared to the methods reported in the specialized literature. This ensures that the parameters estimated by the proposed methodology, in each test transformer, are close to the real value with an accuracy error of less than 6%. Additionally, the computation times required by the algorithm to find the optimal solution are less than 1 second, which makes the proposed HOA robust, reliable, and efficient. All simulations were performed in the MATLAB programming environment. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. |
| publishDate |
2022 |
| dc.date.issued.none.fl_str_mv |
2022 |
| dc.date.accessioned.none.fl_str_mv |
2023-07-21T15:41:17Z |
| dc.date.available.none.fl_str_mv |
2023-07-21T15:41:17Z |
| dc.date.submitted.none.fl_str_mv |
2023 |
| dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_b1a7d7d4d402bcce |
| dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
| dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/article |
| dc.type.hasversion.spa.fl_str_mv |
info:eu-repo/semantics/draft |
| dc.type.spa.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
| status_str |
draft |
| dc.identifier.citation.spa.fl_str_mv |
Cortés-Caicedo, B.; Montoya, O.D.; Arias-Londoño, A. Application of the Hurricane Optimization Algorithm to Estimate Parameters in Single-Phase Transformers Considering Voltage and Current Measures. Computers 2022, 11, 55. https://doi.org/10.3390/computers11040055 |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/12275 |
| dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.3390/computers11040055 |
| dc.identifier.instname.spa.fl_str_mv |
Universidad Tecnológica de Bolívar |
| dc.identifier.reponame.spa.fl_str_mv |
Repositorio Universidad Tecnológica de Bolívar |
| identifier_str_mv |
Cortés-Caicedo, B.; Montoya, O.D.; Arias-Londoño, A. Application of the Hurricane Optimization Algorithm to Estimate Parameters in Single-Phase Transformers Considering Voltage and Current Measures. Computers 2022, 11, 55. https://doi.org/10.3390/computers11040055 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
| url |
https://hdl.handle.net/20.500.12585/12275 https://doi.org/10.3390/computers11040055 |
| dc.language.iso.spa.fl_str_mv |
eng |
| language |
eng |
| dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
| dc.rights.uri.*.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
| dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
| dc.rights.cc.*.fl_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
| rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://purl.org/coar/access_right/c_abf2 |
| eu_rights_str_mv |
openAccess |
| dc.format.extent.none.fl_str_mv |
19 páginas |
| dc.format.mimetype.spa.fl_str_mv |
application/pdf |
| dc.publisher.place.spa.fl_str_mv |
Cartagena de Indias |
| dc.source.spa.fl_str_mv |
Computers 2022, 11, 55 |
| institution |
Universidad Tecnológica de Bolívar |
| bitstream.url.fl_str_mv |
https://repositorio.utb.edu.co/bitstream/20.500.12585/12275/1/computers-11-00055.pdf https://repositorio.utb.edu.co/bitstream/20.500.12585/12275/2/license_rdf https://repositorio.utb.edu.co/bitstream/20.500.12585/12275/3/license.txt https://repositorio.utb.edu.co/bitstream/20.500.12585/12275/4/computers-11-00055.pdf.txt https://repositorio.utb.edu.co/bitstream/20.500.12585/12275/5/computers-11-00055.pdf.jpg |
| bitstream.checksum.fl_str_mv |
c288b4cb67b029bb09eaf66bd572230a 4460e5956bc1d1639be9ae6146a50347 e20ad307a1c5f3f25af9304a7a7c86b6 98b25154b8c8a2eff3e5536d4d51bbbb 5fd5be2836bc6623280c8d7a2aaf8453 |
| bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 MD5 MD5 |
| repository.name.fl_str_mv |
Repositorio Institucional UTB |
| repository.mail.fl_str_mv |
repositorioutb@utb.edu.co |
| _version_ |
1814021693215080448 |
| spelling |
Cortés-Caicedo, Brandon0b676225-338d-48dc-8f2a-694085d9bb42Montoya, Oscar Danilo8a59ede1-6a4a-4d2e-abdc-d0afb14d4480Arias-Londoño, Andrés89909de0-da09-49a3-8e61-83197925ba342023-07-21T15:41:17Z2023-07-21T15:41:17Z20222023Cortés-Caicedo, B.; Montoya, O.D.; Arias-Londoño, A. Application of the Hurricane Optimization Algorithm to Estimate Parameters in Single-Phase Transformers Considering Voltage and Current Measures. Computers 2022, 11, 55. https://doi.org/10.3390/computers11040055https://hdl.handle.net/20.500.12585/12275https://doi.org/10.3390/computers11040055Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarIn this research paper, a combinatorial optimization approach is proposed for parameter estimation in single-phase transformers considering voltage and current measurements at the transformer terminals. This problem is represented through a nonlinear programming model (NLP), whose objective is to minimize the root mean square error between the measured voltage and current values and the calculated values from the equivalent model of the single-phase transformer. These values of voltage and current can be determined by applying Kirchhoff’s Laws to the model T of the transformer, where its parameters, series resistance and reactance as well as the magnetization resistance and reactance, i.e., R1, R′2,X1, X′2,Rc y Xm, are provided by the Hurricane Optimization Algorithm (HOA). The numerical results in the 4 kVA, 10 kVA and 15 kVA single-phase test transformers demonstrate the applicability of the proposed method since it allows the reduction of the average error between the measured and calculated electrical variables by 1000% compared to the methods reported in the specialized literature. This ensures that the parameters estimated by the proposed methodology, in each test transformer, are close to the real value with an accuracy error of less than 6%. Additionally, the computation times required by the algorithm to find the optimal solution are less than 1 second, which makes the proposed HOA robust, reliable, and efficient. All simulations were performed in the MATLAB programming environment. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.19 páginasapplication/pdfenghttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2Computers 2022, 11, 55Application of the Hurricane Optimization Algorithm to Estimate Parameters in Single-Phase Transformers Considering Voltage and Current Measuresinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/drafthttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/version/c_b1a7d7d4d402bccehttp://purl.org/coar/resource_type/c_2df8fbb1Transformer Windings;Frequency Response;Electric PotentialLEMBCartagena de IndiasLöfquist, L. Is there a universal human right to electricity? (2020) International Journal of Human Rights, 24 (6), pp. 711-723. Cited 20 times. http://www.tandfonline.com/toc/fjhr20/current doi: 10.1080/13642987.2019.1671355Sarkodie, S.A., Adams, S. Electricity access, human development index, governance and income inequality in Sub-Saharan Africa (2020) Energy Reports, 6, pp. 455-466. Cited 90 times. http://www.journals.elsevier.com/energy-reports/ doi: 10.1016/j.egyr.2020.02.009Zaghwan, A., Gunawan, I. Energy loss impact in electrical smart grid systems in australia (2021) Sustainability (Switzerland), 13 (13), art. no. 7221. Cited 3 times. https://www.mdpi.com/2071-1050/13/13/7221/pdf doi: 10.3390/su13137221Pinzón, S., Yánez, S., Ruiz, M. Optimal Location of Transformers in Electrical Distribution Networks Using Geographic Information Systems (2020) Enfoque Ute, 11, pp. 84-95. Cited 4 times. [CrossRef]Tabrez, M., Sadhu, P.K., Lipu, M.S.H., Iqbal, A., Husain, M.A., Ansari, S. Power conversion techniques using multi-phase transformer: Configurations, applications, issues and recommendations (2022) Machines, 10 (1), art. no. 13. Cited 6 times. https://www.mdpi.com/2075-1702/10/1/13/pdf doi: 10.3390/machines10010013Bocanegra, S.Y., Montoya, O.D., Molina-Cabrera, A. Parameter estimation in singe-phase transformers employing voltage and current measures (2020) Rev. UIS Ingenierías, 19, pp. 63-75. Cited 7 times. (In Spanish) [CrossRef]Ćalasan, M., Mujičić, D., Rubežić, V., Radulović, M. Estimation of equivalent circuit parameters of single-phase transformer by using chaotic optimization approach (2019) Energies, 12 (9), art. no. 1697. Cited 20 times. https://www.mdpi.com/1996-1073/12/9 doi: 10.3390/en12091697Calasan, M.P., Jovanovic, A., Rubezic, V., Mujicic, D., Deriszadeh, A. Notes on Parameter Estimation for Single-Phase Transformer (2020) IEEE Transactions on Industry Applications, 56 (4), art. no. 9088218, pp. 3710-3718. Cited 16 times. https://ieeexplore.ieee.org/servlet/opac?punumber=28 doi: 10.1109/TIA.2020.2992667Singh, M., Prakasha, A., Meera, K.S. Impact of Online Testing of Distribution Transformers-A Case Study (2019) Proceedings of 2019 International Conference on High Voltage Engineering and Technology, ICHVET 2019, art. no. 8724291. Cited 2 times. http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8716492 ISBN: 978-153867576-2 doi: 10.1109/ICHVET.2019.8724291Foros, J., Istad, M. Health Index, Risk and Remaining Lifetime Estimation of Power Transformers (2020) IEEE Transactions on Power Delivery, 35 (6), art. no. 8999749, pp. 2612-2620. Cited 37 times. https://ieeexplore.ieee.org/servlet/opac?punumber=61 doi: 10.1109/TPWRD.2020.2972976Hamoodi, A.N., Hammad, B.A., Abdullah, F.S. Experimental simulation analysis for single phase transformer tests (Open Access) (2020) Bulletin of Electrical Engineering and Informatics, 9 (3), pp. 862-869. Cited 3 times. http://beei.org/index.php/EEI/article/download/1710/1408 doi: 10.11591/eei.v9i3.1710Krishan, R., Mishra, A.K., Rajpurohit, B.S. Real-time parameter estimation of single-phase transformer (2016) 2016 IEEE 7th Power India International Conference, PIICON 2016, art. no. 8077315. Cited 6 times. ISBN: 978-146738962-4 doi: 10.1109/POWERI.2016.8077315Bocanegra, S.Y., Montoya, O.D., Molina-Cabrera, A. Sine-cosine optimization approach applied to the parametric estimation in single-phase transformers by considering voltage and current measures (2021) DYNA (Colombia), 88 (219), pp. 19-27. Cited 4 times. http://www.scielo.org.co/pdf/dyna/v88n219/2346-2183-dyna-88-219-19.pdf doi: 10.15446/dyna.v88n219.93670Illias, H.A., Mou, K.J., Bakar, A.H.A. Estimation of transformer parameters from nameplate data by imperialist competitive and gravitational search algorithms (2017) Swarm and Evolutionary Computation, 36, pp. 18-26. Cited 26 times. http://www.elsevier.com/wps/find/journaldescription.cws_home/724666/description#description doi: 10.1016/j.swevo.2017.03.003Mossad, M.I., Azab, M., Abu-Siada, A. Transformer parameters estimation from nameplate data using evolutionary programming techniques (Open Access) (2014) IEEE Transactions on Power Delivery, 29 (5), art. no. 6781604, pp. 2118-2123. Cited 42 times. doi: 10.1109/TPWRD.2014.2311153Bhowmick, D., Manna, M., Chowdhury, S.K. Estimation of Equivalent Circuit Parameters of Transformer and Induction Motor Using PSO (Open Access) (2016) IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2016, 2016-January, pp. 1-6. Cited 11 times. doi: 10.1109/PEDES.2016.7914531Yilmaz, Z., Okşar, M., Başçiftçi, F. Multi-objective artificial bee colony algorithm to estimate transformer equivalent circuit parameters (2017) Periodicals of Engineering and Natural Sciences, 5 (3), pp. 271-277. Cited 19 times. http://pen.ius.edu.ba/index.php/pen/article/download/103/141 doi: 10.21533/pen.v5i3.103Abdelwanis, M.I., Abaza, A., El-Sehiemy, R.A., Ibrahim, M.N., Rezk, H. Parameter Estimation of Electric Power Transformers Using Coyote Optimization Algorithm with Experimental Verification (Open Access) (2020) IEEE Access, 8, art. no. 9026962, pp. 50036-50044. Cited 36 times. http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639 doi: 10.1109/ACCESS.2020.2978398Youssef, H., Hassan, M.H., Kamel, S., Elsayed, S.K. Parameter estimation of single phase transformer using jellyfish search optimizer algorithm (Open Access) (2021) 2021 IEEE International Conference on Automation/24th Congress of the Chilean Association of Automatic Control, ICA-ACCA 2021, art. no. 9465279. Cited 13 times. http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=9465172 ISBN: 978-166540127-2 doi: 10.1109/ICAACCA51523.2021.9465279Arenas-Acuña, C.A., Rodriguez-Contreras, J.A., Montoya, O.D., Rivas-Trujillo, E. Black-hole optimization applied to the parametric estimation in distribution transformers considering voltage and current measures (Open Access) (2021) Computers, 10 (10), art. no. 124. Cited 9 times. https://www.mdpi.com/2073-431X/10/10/124/pdf doi: 10.3390/computers10100124Gracia-Velásquez, D.G., Morales-Rodríguez, A.S., Montoya, O.D. Application of the Crow Search Algorithm to the Problem of the Parametric Estimation in Transformers Considering Voltage and Current Measures (Open Access) (2022) Computers, 11 (1), art. no. 9. Cited 4 times. https://www.mdpi.com/2073-431X/11/1/9/pdf doi: 10.3390/computers11010009Adetunji, K.E., Hofsajer, I.W., Abu-Mahfouz, A.M., Cheng, L. A Review of Metaheuristic Techniques for Optimal Integration of Electrical Units in Distribution Networks (Open Access) (2021) IEEE Access, 9, art. no. 9311503, pp. 5046-5068. Cited 22 times. http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639 doi: 10.1109/ACCESS.2020.3048438Devikanniga, D., Vetrivel, K., Badrinath, N. Review of meta-heuristic optimization based artificial neural networks and its applications (Open Access) (2019) Journal of Physics: Conference Series, 1362 (1), art. no. 012074. Cited 31 times. http://iopscience.iop.org/journal/1742-6596 doi: 10.1088/1742-6596/1362/1/012074Rbouh, I., El Imrani, A.A. Hurricane-based optimization algorithm (2014) AASRI Procedia, 6, pp. 26-33. Cited 16 times. [CrossRef]Arteaga, J.A., Montoya, O.D., Grisales-Noreña, L.F. Solution of the optimal power flow problem in direct current grids applying the hurricane optimization algorithm (Open Access) (2020) Journal of Physics: Conference Series, 1448 (1), art. no. 012015. Cited 5 times. http://iopscience.iop.org/journal/1742-6596 doi: 10.1088/1742-6596/1448/1/012015Rizk-Allah, R.M., El-Sehiemy, R.A., Wang, G.-G. A novel parallel hurricane optimization algorithm for secure emission/economic load dispatch solution (2018) Applied Soft Computing Journal, 63, pp. 206-222. Cited 123 times. http://www.elsevier.com/wps/find/journaldescription.cws_home/621920/description#description doi: 10.1016/j.asoc.2017.12.002El-Sehiemy, R.A., Rizk-Allah, R.M., Attia, A.-F. Assessment of hurricane versus sine-cosine optimization algorithms for economic/ecological emissions load dispatch problem (Open Access) (2019) International Transactions on Electrical Energy Systems, 29 (2), art. no. e2716. Cited 28 times. http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2050-7038 doi: 10.1002/etep.2716Cruz-Reyes, J.L., Salcedo-Marcelo, S.S., Montoya, O.D. Application of the Hurricane-Based Optimization Algorithm to the Phase-Balancing Problem in Three-Phase Asymmetric Networks (Open Access) (2022) Computers, 11 (3), art. no. 43. Cited 3 times. https://www.mdpi.com/2073-431X/11/3/43/pdf doi: 10.3390/computers11030043Lenin, K. Solving optimal reactive power problem by hurricane search optimization algorithm (2021) Int. J. Appl. Power Eng. (IJAPE), 10, p. 26. [CrossRef]Baqaruzi, S., Kasim, S.T. Comparison of Effect Efficiency and Voltage Regulation Between Three-Phase Transformer Winding Connections (2020) Bull. Comput. Sci. Electr. Eng, 1, pp. 54-62. [CrossRef]http://purl.org/coar/resource_type/c_6501ORIGINALcomputers-11-00055.pdfcomputers-11-00055.pdfapplication/pdf381533https://repositorio.utb.edu.co/bitstream/20.500.12585/12275/1/computers-11-00055.pdfc288b4cb67b029bb09eaf66bd572230aMD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://repositorio.utb.edu.co/bitstream/20.500.12585/12275/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-83182https://repositorio.utb.edu.co/bitstream/20.500.12585/12275/3/license.txte20ad307a1c5f3f25af9304a7a7c86b6MD53TEXTcomputers-11-00055.pdf.txtcomputers-11-00055.pdf.txtExtracted texttext/plain63592https://repositorio.utb.edu.co/bitstream/20.500.12585/12275/4/computers-11-00055.pdf.txt98b25154b8c8a2eff3e5536d4d51bbbbMD54THUMBNAILcomputers-11-00055.pdf.jpgcomputers-11-00055.pdf.jpgGenerated Thumbnailimage/jpeg7976https://repositorio.utb.edu.co/bitstream/20.500.12585/12275/5/computers-11-00055.pdf.jpg5fd5be2836bc6623280c8d7a2aaf8453MD5520.500.12585/12275oai:repositorio.utb.edu.co:20.500.12585/122752023-07-22 00:17:52.576Repositorio Institucional UTBrepositorioutb@utb.edu.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 |